Adipose or fat tissue plays a key role in lipid storage, glucose homeostasis, and the regulation of energy metabolism; defects in adipose cell function are associated with the development of insulin resistance and type 2 diabetes. Our laboratory uses high-resolution microscopy methods, such as total internal reflection fluorescence and super-resolution localization microscopies, on isolated adipose cells to observe and analyze the fundamental dynamic trafficking events that comprise a response to insulin at the level of individual secretory vesicles and proteins. The trafficking of glucose transporter containing vesicles (GLUT4) to the plasma membrane is an important cellular response to insulin. Systemic insulin responses, such as glucose clearance, represent the integrated GLUT4 translocations of all responding muscle and adipose cells. Genetic, epigenetic, dietary, and lifestyle factors (including exercise) clearly influence population-level adipose cell insulin responsiveness. We have previously shown directly at the GLUT4 trafficking level, populations of isolated human adipose cells in in vitro culture media lacking host serum retain the wide variation in insulin sensitivity of their hosts. However, the relationship between adipose cell heterogeneity and development of insulin resistance may be masked when population responses are measured. The key question that we have addressed now is whether insulin resistance is due to a graded loss of insulin response among all individual cells or if the fraction of cells responding to insulin changes. We have now analyzed the relationship between human adipose cell heterogeneity and subject systemic insulin resistance by taking advantage of the GLUT4 trafficking response data we previously published as average population values for the adipose cells from each subject and demonstrate that a two-component model best describes the relationship between our observations and subject insulin sensitivity. Since isolated cells exhibit these different response characteristics in the presence of constant culture conditions and milieu, we suggest that a physiological switching mechanism at the adipose cellular level ultimately drives systemic insulin sensitivity. To analyze individual adipose cell responses to insulin, we have utilized statistical methods that avoid data averaging and allow us to identify underlying distributions of cellular responses per subject and among the pooled data from a group of subjects with variable insulin sensitivity over a range from normal to at risk. The major difference between cells from insulin-resistant subjects and insulin-sensitive subjects is not the individual cell response amplitude, but rather the number of cells that exhibit a 34 fold response. Simultaneously, in almost every subject, we observed cells that do not exhibit any insulin response that could be statistically distinguished from the typical basal range of values. This observed heterogeneity in the insulin response of individual adipose cells strongly indicates that the underlying distribution is far from normal and thus that simple averaging of the cellular data is not appropriate. We observed two distinct populations for both the insulin-stimulated trafficking parameters (mobility and fusion), with one of these populations coinciding with the basal state; we refer to this latter subpopulation as insulin-refractory. Based on our findings, we proposed that a bimodal cell population comprising two states best models the observed insulin response: insulin-refractory and insulin-responsive adipose cells. Since adipose cells may actually contribute directly to systemic insulin resistance, we determined that the fraction of refractory cells in the insulin-stimulated state increases with increasing values for the insulin resistance seen in our subject population. Whereas the subject insulin sensitivities are best described by a unimodal distribution, the insulin-stimulated refractory fractions for both trafficking parameters are best described by bimodal distributions. A two-component model whose mean values are taken from the refractory fractions better describes the data than a single correlation line and is characteristic of a switch-like function. The fraction of responsive cells decreases with impairment but the decrease is not gradual but sharp/switch-like over the range of sensitivities we have studied. Ultimately, understanding the mechanism of this newly discovered switching process and the determinants of the varying fractional responses to insulin are fundamental to developing interventions that will control the detrimental effects of systemic insulin resistance. We suggest that the physiological switching mechanism at the adipose cellular level may ultimately drive systemic sensitivity to insulin via altered adipose cellular functions such as fuel metabolism and adipokine secretion.